Triple Data Encryption Research Articles

Evaluating the Impact of Latency in a Virtual Private Network Performance Using Different Encryption Algorithm and Hashing

This study analyzes the performance of a network, specifically on advanced encryption standard and Triple data encryption standard when used with secure hash algorithm and Message digest-5 hashing algorithms, when the communication between two communicating nodes is aided by virtual private network connectivity. The study involved two cases; one with AES and the other with 3DES at which each case had a set of two test scenarios which simulated the performance of the selected protocols to simulate the intended scenarios. The simulation scenarios were configuring AES256 with SHA256, AES256 with MD5 and 3DES with SHA256 as well as 3DES with MD5. The simulations carried out measured the latency that impacted the VPN network. Data was collected using network simulation tool “the Ping tool” in an Ubuntu 20.0.1 environment. It is founded that the hashing algorithm SHA256 experienced high Latency compared to MD5 which is contributed by the capacity of processing the hash value by SHA256. Sha256 Produces a hash value that is 266 bits long while MD5 produces a hash value that is 128 bits long, the longer the hash value the longer time is taken to process it. This causes more latency in the network

State‐of‐the‐Art 3DES Pipelined Cryptographic Engine Design Against Side‐Channel Attacks

ABSTRACTIn this paper, a high‐speed, low‐latency, and high‐security hardware‐implemented triple data encryption standard (3DES) cryptographic algorithm is proposed for securing data privacy. In order to achieve a high throughput for the 3DES architecture, the whole circuit is optimized with a 24‐stage pipelined design at first. For breaking the correlation between the processed data and power dissipation of the 3DES circuit against differential power analysis (DPA) attacks, two pseudo‐random number generators (PRNGs) are embedded to randomly alter the number of pipelined stages and data substitution locations within the 3DES circuit, respectively. Under such a circumstance, the proposed 3DES circuit is able to achieve high performance and strong robustness against DPA attacks without causing much overhead. As shown in the results, under the synthesis of SMIC 14‐nm process design kits (PDK), the clock frequency, area, power dissipation, and throughput of the proposed 3DES circuit, respectively, are achieved as 1.2 GHz, 26,435 m2, 21.05 mW, and 64 Gbps. Furthermore, when DPA attacks are executed on the proposed 3DES circuit, the corresponding secret key cannot be revealed even if 2 million plaintexts are enabled. In contrast, only 40,000 plaintexts are adequate to disclose the secret key of a regular pipelined 3DES circuit.

Analysis of Image Encryption using Triple DES

Abstract: Keeping your essential data secure in today’s world is very essential. There are different types of cyber-attacks which attackers can use to exploit your personal or confidential data for their own needs. Cryptography and its algorithms in cybersecurity has been an important part in providing secure methods to hide or encrypt information or sensitive data which only the person who was intended to be send can access it. This paper presents the triple Data Encryption Standard (DES) approach for secure image encryption from malicious users. This paper provides an efficient, easy and secure approach for encryption of images which is essential in today’s scenario.

Cryptographic methods for secured communication in SDN‐based VANETs: A performance analysis

AbstractVehicular ad‐hoc networks (VANETs) support features like comfort, safety, and infotainment, enhancing traffic efficiency. However, traditional VANETs struggle with dynamic and large‐scale networks due to fixed policies and complex architectures, such as constantly changing vehicle positions. Software‐defined networks (SDN) can address these challenges by offering centralized, logical control, making VANETs more flexible and programmable. While SDNs improve VANET efficiency and add security benefits, they also introduce new security risks by incorporating novel technologies and architectural elements. Since VANET services rely heavily on data communication, compromised data (e.g., modified, falsified) could significantly impact driver and vehicle safety, making secure communication vital. Security threats specific to SDNs, like vulnerabilities in centralized control or flow‐based threats exploiting dynamic routing, necessitate robust cryptographic solutions to secure vehicle communications and data exchange. Various cryptographic algorithms, differing in performance, speed, memory requirements, and key sizes, pose challenges in selecting the optimal one for SDN‐based VANETs. This study evaluated seven cryptographic algorithms, including Blowfish, data encryption standard, triple data encryption standard, Rivest–Shamir–Adleman, advanced encryption standard (AES), advanced encryption standard with elliptic curve cryptography (AES‐ECC), and advanced encryption standard with elliptic curve Diffie‐Hellman (AES‐ECDH), in a simulated SDN‐based VANET. The findings show AES‐ECDH as the most effective overall, though the best choice depends on specific deployment scenarios and application needs.

The Evaluation of LSB Steganography on Image File Using 3DES and MD5 Key

Information security is paramount for individuals, companies, and governments. Threats to data confidentiality are increasingly complex, demanding strong protection. Therefore, cryptography and steganography play pivotal roles. This study proposes the utilization of LSB (Least Significant Bit) steganography on image files employing the 3DES (Triple Data Encryption Standard) algorithm. The aim is to facilitate secure transmission and reception of data, including confidential messages, within digital information media. The research methodology involves implementing 3DES + LSB using Image Citra and innovating 3DES + MD5 Hash in .txt files. The results and discussions described include, among others, Pseudocode, Cryptographic Testing, and Steganography Testing. Based on the results of program analysis and testing, it can be concluded that the more messages that are inserted in the image, the more pixel differences there are in the stego image. The more colors in the image to which the message will be inserted, the more pixel differences in the stego image will be. The images that stego objects can present are only images with .png and .jpeg extensions. Testing from the fidelity aspect, the average PSNR obtained is 66,365, meaning that the stego image quality is very good. Testing from the recovery aspect, from 4 tested stego images, showed that messages can be extracted again. Testing of the robustness spec using two attack techniques, namely rotation, and robustness, shows that the message cannot be extracted from the image. Testers of the computation time, from testing 1-1000 characters, show the average time required for computation is about 0.798 seconds.

Multi-objective secure aware workflow scheduling algorithm in cloud computing based on hybrid optimization algorithm

Cloud computing provides the on-demand service of the user with the use of distributed physical machines, in which security has become a challenging factor while performing various tasks. Several methods were developed for the cloud computing workflow scheduling based on optimal resource allocation; still, the security consideration and efficient allocation of the workflow are challenging. Hence, this research introduces a hybrid optimization algorithm based on multi-objective workflow scheduling in the cloud computing environment. The Regressive Whale Water Tasmanian Devil Optimization (RWWTDO) is proposed for the optimal workflow scheduling based on the multi-objective fitness function with nine various factors, like Predicted energy, Quality of service (QoS), Resource utilization, Actual task running time, Bandwidth utilization, Memory capacity, Make span equivalent of the total cost, Task priority, and Trust. Besides, secure data transmission is employed using the triple data encryption standard (3DES) to acquire enhanced security for workflow scheduling. The method’s performance is evaluated using the resource utilization, predicted energy, task scheduling cost, and task scheduling time and acquired the values of 1.00000, 0.16587, 0.00041, and 0.00314, respectively.

Enhancing Communication Security with 3DES and Spread Spectrum Technologies

As society moves towards the digital age, data security has become an increasingly important issue in wireless communication. To address this problem, the use of encryption techniques has become crucial. In this we studied the Triple Data Encryption Standard (3DES) from theory to practical application, and proposes a wireless spread spectrum system utilizing Direct Sequence Spread Spectrum (DSSS) technology, Quadrature Phase Shift Keying (QPSK) modulation, and 3DES encryption/decryption for secure and reliable data transmission. The system is able to efficiently recover the received signal, even in the presence of interference and noise, as demonstrated by the significantly lower Bit Error Rate (BER) of the received signal compared to the original transmitted binary sequence. The effectiveness of the system is demonstrated through simulation results, indicating that it offers a promising solution for wireless communication applications where secure and reliable data transmission is essential.

Efficiently Encryption Decryption schema for Secure File Storage System in Cloud Computing

Cloud computing finds applications in different industries, providing various services and data storage capabilities. While data stored in the cloud can be retrieved based on user requests, data security remains a primary concern. To address these security concerns, a proposed system employs the combined strength of the Triple Data Encryption Standard (AES) and Blowfish algorithms. The lack of robust and efficient secure file storage systems in cloud computing poses significant risks to data confidentiality and integrity.Existing solutions often lack strong encryption mechanisms and reliable server-side encryption and decryption capabilities. This research aims to develop a secure file storage system that leverages server encryption and decryption techniques to ensure data confidentiality, integrity, and access control in cloud environments. The objective is to design a system that effectively protects sensitive files during storage, transmission, and processing, while maintaining efficient data access and retrieval for authorized users. Key Words: Server-Side Encryption, Secure Key Storage Decryption, Encryption, Secure File Storage, Blowfish

Cyber Security Threats and Protection Technologies for Al Rajhi Bank

Technologies are the basis of practically every social action in today's connected world. Although technology has greatly benefited the banking industry, experts have noted the challenges and risks of cybersecurity. A bank can detect, analyze and protect people from these risks thanks to real-time conditions. The majority of financial institutions, including Al Rajhi Bank, are implementing technology in their daily operations as a result of the COVID-19 outbreak [1], which exposes them to cybersecurity issues. The purpose of this project is to investigate and search for encryption algorithms used by Al-Rajhi Bank and what are the most important security attacks that Al-Rajhi Bank faces, as this was done by communicating with an employee in the information technology department at Al-Rajhi Bank, and interviewing. In addition, a literature review of related works, investigation of algorithms and comparison was carried out, in order to verify the efficiency and strength of encryption algorithms in Al-Rajhi Bank and the results of previous works. Al Rajhi Bank's algorithms are very effective and secure, but the various decision-makers believe that as technology develops, financial institutions should think about incorporating other encryption algorithms, like Rivest-Shamir-Adleman (RSA), Triple Data Encryption Standard (TDES), and Twofish algorithms, into their cyber security systems.

A Novel Approach for Enhancement of Blowfish Algorithm by using DES, DCT Methods for Providing, Strong Encryption and Decryption Capabilities

Data safety has evolved into a critical requirement and a duty in modern life. Most of our systems are designed in such a way that it can get hacked, putting our private information at danger. As a result, for numerous safety motives, we utilize various approaches to save as much as possible on this data, regardless of its varied formats, words, photographs, videos, and so on. The data storage capacity of mobile devices is restricted owing to insufficient data storage and processing. In order to develop a safe MCC environment, security concerns must be studied and analysed. This study compares the most widely used symmetric key encryption algorithms, including DES (Data Encryption Standard), Blowfish, TDES (Triple Data Encryption Standard), PRESENT, and KLEIN. The assessment of algorithms is based on attacks, key size, and block size, with the best outcomes in their field.

Medical image encryption using multi chaotic maps

Over the last twenty years, chaos-based encryption has been an increasingly popular way to encrypt and decrypt data using nonlinear dynamics and deterministic chaos. Discrete chaotic systems based on iterative maps have gotten a lot of interest because of their simplicity and speed. In this paper, three kinds of chaotic maps are utilized to build a digital image encryption strategy depending on a chaotic system. These chaotic maps are the logistic map, Arnold Cat’s map, and Baker’s map. In addition to using the triple data encryption standard (3DES) encryption scheme with the chaotic maps mentioned. The results of the experiments revealed that the suggested digital image encryption technique is both efficient and secure, making it ideal for usage in insecure networks. The transmission control protocol (TCP)/internet protocol (IP) protocol was used for the purpose of transferring data from server to client through the network and vice versa.

High-Throughput CBC Mode Crypto Circuit

The objective of this study is to investigate a high-throughput cipher-block chaining (CBC) mode crypto circuit, which can be embedded in commercial home gateways or switches/routers. Concurrently, the area efficiency of block ciphers can be improved as well. However, the CBC mode encounters the problem of data dependency. To solve this issue, a data scheduling mechanism of network packets is proposed to eliminate the data dependency of input data for CBC mode pipelined crypto engines. The proposed CBC mode architecture can be applied to advanced encryption standards (AES), triple data encryption standards (3DES), and other block ciphers. In addition, to increase the throughput, deeply pipelined AES-CBC and 3DES-CBC circuits with balanced paths are proposed. With the proposed scheduling and pipelined circuits, the authors can effectively encrypt the packet data of multiple network channels at the same time. Using the proposed architecture, throughputs of 137.8 and 44.75 Gbps using a copy of pipelined AES-CBC and 3DES-CBC circuits can be achieved in TSMC 45 nm and TSMC 130 nm processes, respectively.

The Design and Implementation of a Secure File Storage on the Cloud using Hybrid Cryptography

In recent years, cloud computing has become a popular way of storing and sharing data. However, security concerns have been raised about the safety of sensitive information stored on the cloud. Hybrid cryptography, which combines symmetric and asymmetric encryption, has been proposed as a solution to these concerns. This paper proposes a new hybrid cryptography approach for secure file storage on the cloud regardless of the type of deployment model i.e., either public cloud, private cloud, or hybrid cloud. The proposed approach uses a combination of the Advanced Encryption Standard (AES) algorithm, Triple Data Encryption Standard (DES) algorithm, and Rivest cipher 6 (RC6) algorithms are used to provide block-wise security to data. LSB steganography technique is introduced for key information security.

Security of private cloud using machine learning and cryptography

There are increased security challenges that target cloud systems. One of the most important requirements of users in cloud storage is protecting their cloud from attacks and keeping data secure. Modern technologies of machine learning are providing the ability to analyze and classify data perfectly. This paper proposes a model placed between users and the cloud, which is based on two phases. The first of which is protecting the cloud from different types of network attacks and detecting normal and abnormal flow. The second one is categorizing the users' data and then encrypting it based on its importance using different encryption algorithms. The accuracy results of random forest (RF) and decision tree (DT) are 100% of attack detection for each one. For the second phase of classifying data, the algorithms used are the logistic regression (LR) and stochastic gradient descent (SGD) learning which resulted in 98% accuracy for both. Besides, the encryption algorithms that have been adopted are rivest cipher (RC4), triple data encryption (3DES), and advanced encryption standard (AES) for encryption of the classified data according to the importance which will be then stored in the cloud in its secure form.

Block Ciphers Analysis Based on a Fully Connected Neural Network

With the development of high-speed network technologies, there has been a recent rise in the transfer of significant amounts of sensitive data across the Internet and other open channels. The data will be encrypted using the same key for both Triple Data Encryption Standard (TDES) and Advanced Encryption Standard (AES), with block cipher modes called cipher Block Chaining (CBC) and Electronic CodeBook (ECB). Block ciphers are often used for secure data storage in fixed hard drives, portable devices, and safe network data transport. Therefore, to assess the security of the encryption method, it is necessary to become familiar with and evaluate the algorithms of cryptographic systems. Block cipher users need to be sure that the ciphers they employ are secure against various attacks. A Fully Connected Neural Network (FCNN) model was initially used to assess how well the models were classified. Then, all models, including encoder models, were assessed using True Positive (TP) measures for successful classification of the discovered encoder and False Positive (FP) measures for imprecise categorization. The accuracy value, retrieval, loss, precision value, and F1 score were then calculated using a confusion matrix to assess the model's efficacy (abbreviated as F1). ECB results with an accuracy of 85% and CBC results with an accuracy of 88% were produced, and the parameters of the FCNN model were tweaked to provide better results. These results helped to identify the encryption algorithm more precisely and evaluate it.

Proposed system for data security in distributed computing in using ‎triple data encryption standard and ‎Rivest Shamir ‎Adlemen

<span lang="EN-US">Cloud computing is considered a distributed computing paradigm in which resources ‎are ‎provided as services. In cloud computing, the ‎applications do not run ‎from a user’s personal computer but are run and stored on distributed ‎servers on the Internet. The ‎resources of the cloud infrastructures are shared on cloud ‎computing on the Internet in the open ‎environment. This increases the security problems in ‎security such as data confidentiality, data ‎integrity and data availability, so the solution of such ‎problems are conducted by adopting data ‎encryption is very important for securing users data. ‎In this paper, a comparative ‎study is done between the two security algorithms on a cloud ‎platform called eyeOS. From the ‎comparative study it was found that the Rivest Shamir ‎Adlemen ‎(3kRSA) algorithm ‎outperforms that triple data encryption standard (3DES) algorithm with ‎respect to the complexity, and output bytes. The main ‎drawback of the 3kRSA algorithm is its ‎computation time, while 3DES is faster than that ‎‎3kRSA. This is useful for storing large amounts of ‎data used in the cloud computing, the key ‎distribution and authentication of the asymmetric ‎encryption, speed, data integrity and data ‎confidentiality of the symmetric encryption are also ‎important also it enables to execute ‎required computations on this encrypted data.‎</span>

An IoT enabled secured clinical health care framework for diagnosis of heart diseases

World Health Organization (WHO) estimated cardiovascular diseases (CVDs) is main contributor to the death count globally. In addition, there are shortcomings of specialists in developing countries to handle these diseases. Internet of things (IoT) and significant advances in machine learning techniques offers more efficient healthcare services. The research work proposed a IoT enabled, cloud-centric solution for remote monitoring of ECG, which could save lives of rural area people particularly in Golden hour. Firstly, pre-processing of ECG signal is performed using Savitzky-Golay (SG filter) for removal of the baseline wanders and maximum overlap discrete wavelet packet transform (MOWPT) is applied for the removal of high noise followed by delineation process of ECG characteristic points. Then deep learned convolution neural network (CNN) is trained and classification is done. For encryption and authentication, Triple data encryption standard is used for security whereas, water cycle optimization technique is used for authentication. IoT is implemented using the ThingSpeak platform, which enables the visualization and analysed the ECG data over the cloud server. Using ThingSpeak, encrypted and authenticated ECG data is shared with cardiologist for examination. To validate the proposed classification method, the standard annotated dataset of the MIT-BIH database is tested and various performance metrics were calculated. The proposed deep learned CNN classifier classifies the heartbeats into five types of arrhythmias with an average accuracy of 99.12%, whereas the sensitivity and specificity of this proposed model are 100% and 99.9% respectively. The achieved results demonstrated better performance as compared to methods reported in the literature.

An Efficient and Secure Big Data Storage in Cloud Environment by Using Triple Data Encryption Standard

In recent decades, big data analysis has become the most important research topic. Hence, big data security offers Cloud application security and monitoring to host highly sensitive data to support Cloud platforms. However, the privacy and security of big data has become an emerging issue that restricts the organization to utilize Cloud services. The existing privacy preserving approaches showed several drawbacks such as a lack of data privacy and accurate data analysis, a lack of efficiency of performance, and completely rely on third party. In order to overcome such an issue, the Triple Data Encryption Standard (TDES) methodology is proposed to provide security for big data in the Cloud environment. The proposed TDES methodology provides a relatively simpler technique by increasing the sizes of keys in Data Encryption Standard (DES) to protect against attacks and defend the privacy of data. The experimental results showed that the proposed TDES method is effective in providing security and privacy to big healthcare data in the Cloud environment. The proposed TDES methodology showed less encryption and decryption time compared to the existing Intelligent Framework for Healthcare Data Security (IFHDS) method.

Secure Data Sharing Using 3DES Algorithm

Abstract: The Triple Data Encryption Algorithm, also known as Triple DES (Data Encryption Standard), 3DES, TDES, Triple DEA, or TDEA, is a symmetric key-block cypher that uses the DES cypher in triplicate by encrypting with key 1 (k1), decrypting with key 2, and encrypting with key 3 (k3) (k3). There is a two-key variation as well, where k1 and k3 are identical. The Data Encryption Standard, created by IBM in the early 1970s and adopted by NIST with minor adjustments in 1977, is the foundation of the 3DES cypher suite. The system consists of a Data Owner, Network Storage, Aggregate Key and User. The data owner uploads the file which is encrypted by making use of 3DES algorithm, once the data has been encrypted blowfish is applied to convert the whole data into data blocks which is stored in network storage or the drop box. When the authorized user provides the secret key that is the aggregate key the data is decrypted and original data is available for the user. Admin will be a superuser who will manage different things like uploaded files and registered users. Admin will be having permissions to remove users if found invalid. The secure data sharing system using 3DES algorithm is developed with the Java technologies. Encryption is done using triple standard encryption standard. Agile methodology is used to develop the system and MySQL Database is used to store the data. The system is able to efficiently store the data uploaded by the data owner after encrypting it using blowfish algorithm and 3DES technology. After the storage of the data the system will also be able to securely transfer the saved data within the trusted set of people without any other person able to access the file.

A Novel Algorithm to Secure Data in New Generation Health Care System from Cyber Attacks Using IoT

The rise of digital technology has essentially enhanced the overall communication and data management system, facilitating essential medical care services. Considering this aspect, the healthcare system successfully managed patient requirements through online services and facilitated patient experience. However, the lack of adequate data security and increased digital activities during Covid-19 made the healthcare system a soft target for hackers to gain unauthorized access and steal crucial and sensitive information. Countries such as the UK and the US recently received such challenges, highlighting the need for effective data maintenance. IoT emerged as one of the critical solutions for data management systems in terms of addressing data security which certainly can enhance overall data collection, storage, maintenance, prediction of potential data security breaches and taking appropriate measurements. The concerned research considers a secondary data collection process where necessary data is collected from original scholarly articles, books and journals. Apart from that, a positivism research philosophy, a deductive research approach and a descriptive research design have been considered for this study. Qualitative data analysis techniques have also been incorporated into this research. Upon viewing the pros and cons of IoT algorithms, DES, AES, triple data encryption standards, and RSA encryption can be used in the healthcare system to facilitate data protection.